Development and Evaluation of a Highly Scalable News Recommender System. - Ilya Verbitskiy; Patrick Probst; Andreas Lommatzsch (CLEF (Working Notes), 2015)

Selecting resources for distributed dataflow systems according to runtime targets. - Lauritz Thamsen; Ilya Verbitskiy; Florian Schmidt 006; Thomas Renner; Odej Kao (IPCCC, 2016)

When to Use a Distributed Dataflow Engine: Evaluating the Performance of Apache Flink. - Ilya Verbitskiy; Lauritz Thamsen; Odej Kao (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld, 2016)

Ellis: Dynamically Scaling Distributed Dataflows to Meet Runtime Targets. - Lauritz Thamsen; Ilya Verbitskiy; Jossekin Beilharz; Thomas Renner; Andreas Polze; Odej Kao (CloudCom, 2017)

Adaptive Resource Management for Distributed Data Analytics. - Lauritz Thamsen; Thomas Renner; Ilya Verbitskiy; Odej Kao (TopHPC, 2017)

Scheduling Stream Processing Tasks on Geo-Distributed Heterogeneous Resources. - Gerrit Jansen; Ilya Verbitskiy; Thomas Renner; Lauritz Thamsen (IEEE BigData, 2018)

CoBell: Runtime Prediction for Distributed Dataflow Jobs in Shared Clusters. - Ilya Verbitskiy; Lauritz Thamsen; Thomas Renner; Odej Kao (CloudCom, 2018)

Multilayer Active Learning for Efficient Learning and Resource Usage in Distributed IoT Architectures. - Sasho Nedelkoski; Lauritz Thamsen; Ilya Verbitskiy; Odej Kao (EDGE, 2019)

Hugo: A Cluster Scheduler that Efficiently Learns to Select Complementary Data-Parallel Jobs. - Lauritz Thamsen; Ilya Verbitskiy; Sasho Nedelkoski; Vinh Thuy Tran; Vinícius Meyer; Miguel G. Xavier; Odej Kao; César A. F. De Rose (Euro-Par Workshops, 2019)